215, including, but not limited to, random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), fast page mode dynamic random access memory (FPM DRAM), extended data-out dynamic random access memory (EDO DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), double data rate type two synchronous dynamic random access memory (DDR2 SDRAM), double data rate type three synchronous dynamic random access memory (DDR3 SDRAM), Rambus dynamic random access memory (RDRAM), Twin Transistor RAM (TTRAM), Thyristor RAM (T-RAM), Zero-capacitor (Z-RAM), Rambus in-line memory module (RIMM), dual in-line memory module (DIMM), single in-line memory module (SIMM), video random access memory (VRAM), cache memory, register memory, and/or the like.

As will be recognized, the volatile storage or memory media may be used to store at least portions of the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like being executed by, for example, the processing element 205. Thus, the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like may be used to control certain aspects of the operation of the data analysis computing entity 106 with the assistance of the processing element 205 and operating system.

As indicated, in some embodiments, the data analysis computing entity 106 may also include one or more network interfaces 220 for communicating with various computing entities, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like. Such communication may be executed using a wired data transmission protocol, such as fiber distributed data interface (FDDI), digital subscriber line (DSL), Ethernet, asynchronous transfer mode (ATM), frame relay, data over cable service interface specification (DOCSIS), or any other wired transmission protocol. Similarly, the data analysis computing entity 106 may be configured to communicate via wireless external communication networks using any of a variety of protocols, such as general packet radio service (GPRS), Universal Mobile Telecommunications System (UMTS), Code Division Multiple Access 2000 (CDMA2000), CDMA2000 1× (1×RTT), Wideband Code Division Multiple Access (WCDMA), Global System for Mobile Communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), Time Division-Synchronous Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Evolved Universal Terrestrial Radio Access Network (E-UTRAN), Evolution-Data Optimized (EVDO), High Speed Packet Access (HSPA), High-Speed Downlink Packet Access (HSDPA), IEEE 802.11 (Wi-Fi), Wi-Fi Direct, 802.16 (WiMAX), ultra-wideband (UWB), infrared (IR) protocols, near field communication (NFC) protocols, Wibree, Bluetooth protocols, wireless universal serial bus (USB) protocols, and/or any other wireless protocol.

Although not shown, the data analysis computing entity 106 may include, or be in communication with, one or more input elements, such as a keyboard input, a mouse input, a touch screen/display input, motion input, movement input, audio input, pointing device input, joystick input, keypad input, and/or the like. The data analysis computing entity 106 may also include, or be in communication with, one or more output elements (not shown), such as audio output, video output, screen/display output, motion output, movement output, and/or the like.

FIG. 3 provides an illustrative schematic representative of an mmWave RFID reader computing entity 102 that can be used in conjunction with embodiments of the present disclosure. In general, the terms device, system, computing entity, entity, and/or similar words used herein interchangeably may refer to, for example, one or more computers, computing entities, desktops, mobile phones, tablets, phablets, notebooks, laptops, distributed systems, kiosks, input terminals, servers or server networks, blades, gateways, switches, processing devices, processing entities, set-top boxes, relays, routers, network access points, base stations, the like, and/or any combination of devices or entities adapted to perform the functions, operations, and/or processes described herein. As shown in FIG. 3, the mmWave RFID reader computing entities 102 can include one or more antenna units 312, one or more transmitters 304 (e.g., radio), one or more receivers 306 (e.g., radio), and a processing element 308 (e.g., CPLDs, microprocessors, multi-core processors, coprocessing entities, ASIPs, microcontrollers, and/or controllers) that provides signals to and receives signals from the one or more transmitters 304 and the one or more receivers 306, correspondingly. In some embodiments, the mmWave RFID reader computing entities 102 the one or more antenna units 312, the one or more transmitters 304, and the one or more receivers 306 may be dedicated to communications with specific entities. For example, a first set of the one or more antenna units 312, the one or more transmitters 304, and the one or more receivers 306 may be dedicated for communications with data analysis computing entity 106, and a second set of the one or more antenna units 312, the one or more transmitters 304, and the one or more receivers 306 may be dedicated for communications with RFID tags and a radiolocation sensor (e.g., mmWave).

The signals provided to and received from the one or more transmitters 304 and the one or more receivers 306, correspondingly, may include signaling information/data in accordance with air interface standards of applicable wireless systems. In this regard, the mmWave RFID reader computing entity 102 may be capable of operating with one or more air interface standards, communication protocols, modulation types, and access types. More particularly, the mmWave RFID reader computing entity 102 may operate in accordance with any of a number of wireless communication standards and protocols, such as those described above with regard to the data analysis computing entity 106. In some embodiments, the mmWave RFID reader computing entity 102 may operate in accordance with multiple wireless communication standards and protocols, such as UMTS, CDMA2000, 1×RTT, WCDMA, GSM, EDGE, TD-SCDMA, LTE, E-UTRAN, EVDO, HSPA, HSDPA, Wi-Fi, Wi-Fi Direct, WiMAX, UWB, IR, NFC, Bluetooth, USB, RFID, and/or the like. Similarly, the mmWave RFID reader computing entity 102 may operate in accordance with multiple wired communication standards and protocols, such as those described above with regard to the data analysis computing entity 106 via a network interface 320.

Via the aforementioned communication standards and protocols, the mmWave RFID reader computing entity 102 can communicate with various entities, such as data analysis computing entity 106 using mechanisms such as Unstructured Supplementary Service Data (USSD), Short Message Service (SMS), Multimedia Messaging Service (MMS), Dual-Tone Multi-Frequency Signaling (DTMF), and/or Subscriber Identity Module Dialer (SIM dialer). The mmWave RFID reader computing entity 102 can also download changes, add-ons, and updates, for instance, to its firmware, software (e.g., including executable instructions, applications, program modules), and operating system.

According to some embodiments, the mmWave RFID reader computing entity 102 may include location determining aspects, devices, modules, functionalities, and/or similar words used herein interchangeably. For example, the mmWave RFID reader computing entity 102 may include indoor positioning aspects, such as a location module adapted to acquire, for example, latitude, longitude, altitude, geocode, course, direction, heading, speed, time, date, and/or various other information/data. Some of the indoor systems may use various position or location technologies including RFID tags, indoor beacons or transmitters, Wi-Fi access points, cellular towers, nearby computing devices (e.g., smartphones, laptops), and/or the like. For instance, such technologies may include the iBeacons, Gimbal proximity beacons, Bluetooth Low Energy (BLE) transmitters, NFC transmitters, and/or the like. These indoor positioning aspects can be used in a variety of settings to determine the location of someone or something to within inches or centimeters.

The mmWave RFID reader computing entity 102 may also comprise a user interface (that can include a display 316 coupled to a processing element 308) and/or a user input interface (coupled to a processing element 308). For example, the user interface may be a user application, browser, user interface, and/or similar words used herein interchangeably executing on and/or accessible via the mmWave RFID reader computing entity 102 to interact with and/or cause display of information/data from the data analysis computing entity 106, as described herein. The user input interface can comprise any of a number of devices or interfaces allowing the mmWave RFID reader computing entity 102 to receive data, such as a keypad 318 (hard or soft), a touch display, voice/speech or motion interfaces, or other input device. In embodiments including a keypad 318, the keypad 318 can include (or cause display of) the conventional numeric (0-9) and related keys (#, *), and other keys used for operating the mmWave RFID reader computing entity 102 and may include a full set of alphabetic keys or set of keys that may be activated to provide a full set of alphanumeric keys. In addition to providing input, the user input interface can be used, for example, to activate or deactivate certain functions, such as screen savers and/or sleep modes.

The mmWave RFID reader computing entity 102 can also include volatile memory 322 and/or non-volatile memory 324, which can be embedded and/or may be removable. For example, the non-volatile memory 324 may be ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM, FeRAM, NVRAM, MRAM, RRAM, SONOS, FJG RAM, Millipede memory, racetrack memory, and/or the like. The volatile memory 322 may be RAM, DRAM, SRAM, FPM DRAM, EDO DRAM, SDRAM, DDR SDRAM, DDR2 SDRAM, DDR3 SDRAM, RDRAM, TTRAM, T-RAM, Z-RAM, RIMM, DIMM, SIMM, VRAM, cache memory, register memory, and/or the like. The volatile and non-volatile memory can store databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like to implement the functions of the mmWave RFID reader computing entity 102. As indicated, this may include a user application that is resident on the mmWave RFID reader computing entity 102 or accessible through a browser or other user interface for communicating with the data analysis computing entity 106 and/or various other computing entities.

In another embodiment, the mmWave RFID reader computing entity 102 may include one or more components or functionalities that are the same or similar to those of the data analysis computing entity 106, as described in greater detail above. As will be recognized, these architectures and descriptions are provided for example purposes only and are not limiting to the various embodiments.

In various embodiments, the mmWave RFID reader computing entity 102 may be embodied as an artificial intelligence (AI) computing entity, such as an Amazon Echo, Amazon Echo Dot, Amazon Show, Google Home, and/or the like. Accordingly, the mmWave RFID reader computing entity 102 may be configured to provide and/or receive information/data from a user via an input/output mechanism, such as a display, a camera, a speaker, a voice-activated input, and/or the like. In certain embodiments, an AI computing entity may comprise one or more predefined and executable program algorithms stored within an onboard memory storage module, and/or accessible over a network. In various embodiments, the AI computing entity may be configured to retrieve and/or execute one or more of the predefined program algorithms upon the occurrence of a predefined trigger event.

FIG. 4 provides an illustrative schematic representative of an example one of the one or more antenna units 312 that can be used in conjunction with embodiments of the present disclosure for receiving RFID tag data and point cloud position data. Antenna unit 312-1 may be configured to communicate with mmWave RFID reader computing entity 102 via an air interface standard, such as electronic product code (EPC) generation 2 or any other RFID standard protocols. As depicted in FIG. 4, antenna unit 312-1 comprises a coupler 402, a radio frequency (RF) switch 404, and an RFID integrated circuit (IC) 406. Coupler 402 may comprise a directional coupler configured to (i) split signal output from mmWave RFID reader computing entity 102 to the RF switch 404 and the RFID IC 406 and (ii) combine discrete signals from RF switch 404 and RFID IC 406 to feed a single line to mmWave RFID reader computing entity 102. In some embodiments, the mmWave RFID reader computing entity 102 may be coupled to an input port of coupler 402, RF switch 404 may be coupled to a through port of coupler 402, and RFID IC 406 may be coupled to a coupled port of coupler 402.

RFID IC 406 may be configured to operate as an antenna controller. In some embodiments, RFID IC 406 may be configured to select an antenna for RFID scanning based on read instruction signals from mmWave RFID reader computing entity 102. For example, RFID IC 406 may receive instructions from mmWave RFID reader computing entity 102 to cycle between local beam steering antenna 408 and switch antenna 414. RF switch 404 may be switched by RFID IC 406 to enable routing of RF signals either through local beam steering antenna 408 or switch antenna 414.

In some embodiments, the mmWave RFID reader computing entity 102 may access antenna unit 312-1 to scan locations covered by local beam steering antenna 408 for RFID tags. In some embodiments, local beam steering antenna 408 may comprise an antenna at an immediate location coincident with antenna unit 312-1. For example, antenna unit 312-1 comprising local beam steering antenna 408 may be disposed overhead a location in an indoor environment. The location may comprise one or more beam zone regions covered by local beam steering antenna 408. An overhead position may be supported either vertically or horizontally mounted to the upper structure or the lower structure of a given environment. Additionally, antenna unit 312-1 could be suspended overhead supported by a fixture placed on the floor.

In some embodiments, the mmWave RFID reader computing entity 102 may access antenna unit 312-1 to relay RF signals between mmWave RFID reader computing entity 102 and switch antenna 414 for scanning locations covered by switch antenna 414 for RFID tags and point cloud position data. In some embodiments, switch antenna 414 may be at a location comprising one or more other beam zone regions remote from antenna unit 312-1. Switch antenna 414 may comprise or be coupled to components substantially similar to those comprised in antenna unit 312-1.

Antenna unit 312-1 further comprises an MPU 410 and a mmWave antenna element 412 coupled to the MPU 410. MPU 410 may scan, using the millimeter-wave band, a location coincident with the local beam steering antenna 408 via mmWave antenna element 412 for detecting objects (e.g., shoppers, merchandise, or shopping carts/baskets) and providing range, velocity, and angle of those objects in the form of point cloud position data. In some embodiments, the mmWave antenna element 412 comprises a four-element mmWave radar antenna. Generally, the millimeter wave may refer to an electromagnetic wave in the frequency domain of approximately 24-300 GHz. RFID IC 406 may be coupled to MPU 410 via an interface, such as serial peripheral interface (SPI), in a manner that allows mmWave RFID reader computing entity 102 to read data (e.g., point cloud position data) from MPU 410 through RFID IC 406.

FIG. 5 depicts example components of MPU 410 and mmWave antenna element 412. The mmWave antenna element 412 comprises a transmitting antenna 502, a receiving antenna 504, a frequency synthesizer 506, and a mixer 508. The Doppler principle may be used to determine motion, range, speed, and direction of object 510. In some embodiments, MPU 410 and a mmWave antenna element 412 may employ frequency-modulated continuous wave (FMCW). FMCW may comprise transmitting a frequency-modulated signal continuously in order to measure range as well as angle and velocity. Transmitting antenna 502 may be configured to emit a radar signal generated by the frequency synthesizer 506 with a frequency that increases continuously to create a signal sweep. Frequency synthesizer 506 may comprise an electronic circuit that uses an oscillator to generate a preprogrammed set of stable frequencies with minimal phase noise.

A radar signal transmitted from transmitting antenna 502 may be reflected by object 510, and as such, the signal's echo may be received by the receiving antenna 504. Mixer 508 may combine the radar signal generated by the frequency synthesizer 506 and transmitted from the transmitting antenna 502) with the echo signal received by the receiving antenna 504 to generate an intermediate frequency (IF) signal 512 comprising a difference between the transmitted signal and the echo signal (e.g., the Doppler shift). Echo signals received by the receiving antenna 504 may comprise a frequency difference, referred to as the Doppler frequency. That is, if object 510 is not stationary, the echo signal received by the receiving antenna 504 may comprise a change in frequency from that of the signal transmitted from the transmitting antenna 502. The Doppler frequency may be used to detect movement, velocity, and distance.

MPU 410 is coupled to the mmWave antenna element 412 and receives the IF signal 512 from mixer 508. MPU 410 comprises a low-pass (LP) filter 514, an analog-to-digital converter (ADC) 516, and a fast Fourier transform (FFT) signal processing module 518. The IF signal 512 may be passed through the LP filter 514 and the ADC 516 before being processed by the FFT signal processing module 518 to generate point cloud position data 520.

FIG. 6 depicts an overhead view of at least a portion of an example shopper tracking system 600 deployed in a retail store according to one embodiment of the present disclosure. The shopper tracking system 600 depicted in FIG. 6 may be used to autonomously track movement of objects, such as shoppers, merchandise, or shopping carts/baskets, at a retail store that shoppers (e.g., actors within a local environment) visit to view, select and purchase products. A retail store may position numerous products throughout a sales floor that are to be sold and/or distributed to shoppers. The retail store may be any size or format, and may include products from one or more merchants. For example, the retail store may be a single store operated by one merchant, a chain of two or more stores operated by one entity, or may be one of a collection of stores covering multiple merchants.

The depicted shopper tracking system 600 comprises a plurality of mmWave RFID reader computing entities 602(A,B), a plurality of antenna units 604(A-H), a plurality of switch antennas 606, a data analysis computing entity 608, and a plurality of RFID desktop readers 610(A,B). The mmWave RFID reader computing entities 602 may comprise overhead readers coupled to the plurality of antenna units 604 and switch antennas 606, which may be positioned at fixed locations throughout the retail store for detecting RFID signals from multiple RFID tags as well as position data of objects within the retail store. As such, objects (e.g., people, carts, or baskets) moving within the retail store may pass within scanning range of the plurality of antenna units 604 and switch antennas 606. The RFID desktop readers 610 may comprise readers for detecting RFID signals from RFID tags that within a shorter range than that of the plurality of antenna units 604 and switch antennas 606, and may be intended for an implicit transaction, such as price check, check-out, or purchase. RFID tags may be affixed to or incorporated into and/or affixed to items, or packaging of items being sold from the retail store (e.g., boxed food items, canned food items, cleaning supply items, produce items, frozen food items, consumer electronic goods, health products, beauty products, apparel, and other such items) that are positioned on shelves, modulars, racks, or endcaps, for example.

Data analysis computing entity 608 may be configured to monitor paths of travel of shoppers through a retail establishment, where each shopping cart and/or shopping basket of a retail establishment may be affixed with a RFID tag. For example, during operation, mmWave RFID reader computing entities 602 may scan via the plurality of antenna units 604 to identify from which beam zone a shopping cart RFID tag X₁is being read and generate point cloud position data to identify a shopper X₂in a first zone. Scanning of beam zones is described in further detail with respect to the description of FIG. 7.

The mmWave RFID reader computing entities 602 may transmit X₁and X₂to data analysis computing entity 608 to conjugate location of X₂along with the shopping cart RFID tag X₁. Shopper X₂may pick a merchandise Y₁being read by antenna units 604, where merchandise Y₁may be identified to being in proximity with the shopping cart RFID tag X₁, then data analysis computing entity 608 may assign merchandise Y